公开(公告)号：US08520928B2

公开(公告)日：2013-08-27

申请号：US13104255

申请日：2011-05-10

申请人： Ali Bilgin ,  Yookyung Kim ,  Mariappan S. Nadar ,  Rajagopalan Sundaresan

发明人： Ali Bilgin ,  Yookyung Kim ,  Mariappan S. Nadar ,  Rajagopalan Sundaresan

IPC分类号： G06K9/00

CPC分类号： H04N19/577 ,  H04N19/61

摘要： A method for reconstructing a digital image from a set of measurements includes providing a previous image frame in a time series of measurements of an image signal and a current image frame in the time series, calculating an estimated motion vector for a spatial point and current time point between the previous and current image frames, calculating a motion compensated current image frame from the previous image frame, estimating a known support set of a sparse signal estimate of the motion compensated current image frame where the support set comprises indices of non-zero elements of the sparse signal estimate, calculating a sparse signal corresponding to the current image frame whose support contains a smallest number of new additions to the known support set while satisfying a data consistency constraint, and correcting the motion compensated current image frame image frame from the sparse signal.

摘要翻译： 一种用于从一组测量重建数字图像的方法包括在时间序列中以图像信号和当前图像帧的时间序列测量的时间序列提供先前的图像帧，计算空间点和当前时间的估计的运动矢量 在先前图像帧和当前图像帧之间，从前一图像帧计算运动补偿当前图像帧，估计运动补偿当前图像帧的稀疏信号估计的已知支持集合，其中支持集合包括非零元素的索引 的稀疏信号估计，计算对应于当前图像帧的稀疏信号，其支持在满足数据一致性约束的同时包含对已知支持集合的最小数量的新加法，并且从稀疏信息校正运动补偿的当前图像帧图像帧 信号。

公开(公告)号：US20120008844A1

公开(公告)日：2012-01-12

申请号：US13104255

申请日：2011-05-10

申请人： Ali Bilgin ,  Yookyung Kim ,  Mariappan S. Nadar ,  Rajagopalan Sundaresan

发明人： Ali Bilgin ,  Yookyung Kim ,  Mariappan S. Nadar ,  Rajagopalan Sundaresan

IPC分类号： G06K9/00

CPC分类号： H04N19/577 ,  H04N19/61

摘要： A method for reconstructing a digital image from a set of measurements includes providing a previous image frame in a time series of measurements of an image signal and a current image frame in the time series, calculating an estimated motion vector for a spatial point and current time point between the previous and current image frames, calculating a motion compensated current image frame from the previous image frame, estimating a known support set of a sparse signal estimate of the motion compensated current image frame where the support set comprises indices of non-zero elements of the sparse signal estimate, calculating a sparse signal corresponding to the current image frame whose support contains a smallest number of new additions to the known support set while satisfying a data consistency constraint, and correcting the motion compensated current image frame image frame from the sparse signal.

摘要翻译： 一种用于从一组测量重建数字图像的方法包括在时间序列中以图像信号和当前图像帧的时间序列测量的时间序列提供先前的图像帧，计算空间点和当前时间的估计的运动矢量 在先前图像帧和当前图像帧之间，从前一图像帧计算运动补偿当前图像帧，估计运动补偿当前图像帧的稀疏信号估计的已知支持集合，其中支持集合包括非零元素的索引 的稀疏信号估计，计算对应于当前图像帧的稀疏信号，其支持在满足数据一致性约束的同时包含对已知支持集合的最小数量的新加法，并且从稀疏信息校正运动补偿的当前图像帧图像帧 信号。

公开(公告)号：US20110116724A1

公开(公告)日：2011-05-19

申请号：US12942427

申请日：2010-11-09

申请人： Ali Bilgin ,  Yookyung Kim ,  Mariappan S. Nadar

发明人： Ali Bilgin ,  Yookyung Kim ,  Mariappan S. Nadar

IPC分类号： G06K9/36

CPC分类号： G01R33/5608 ,  G06T11/006 ,  G06T2211/424

摘要： A method for constructing an image includes acquiring image data in a first domain. The acquired image data is transformed from the first domain into a second domain in which the acquired image data exhibits a high degree of sparsity. An initial set of transform coefficients is approximated for transforming the image data from the second domain into a third domain in which the image may be displayed. The approximated initial set of transform coefficients is updated based on a weighing of where substantial transform coefficients are likely to be located relative to the initial set of transform coefficients. An image is constructed in the third domain based on the updated set of transform coefficients. The constructed image is displayed.

摘要翻译： 一种用于构建图像的方法包括获取第一域中的图像数据。 所获取的图像数据从第一域变换到第二域，其中所获取的图像数据表现出高度的稀疏性。 近似变换系数的初始集合，用于将来自第二域的图像数据变换成可以显示图像的第三域。 基于对相对于初始变换系数集合可能存在实质变换系数的权重来更新近似初始变换系数集合。 基于更新的变换系数组，在第三域中构建图像。 显示构图。

公开(公告)号：US08760572B2

公开(公告)日：2014-06-24

申请号：US12942427

申请日：2010-11-09

申请人： Ali Bilgin ,  Yookyung Kim ,  Mariappan S. Nadar

发明人： Ali Bilgin ,  Yookyung Kim ,  Mariappan S. Nadar

IPC分类号： H04N7/12 ,  G06K9/00

CPC分类号： G01R33/5608 ,  G06T11/006 ,  G06T2211/424

摘要： A method for constructing an image includes acquiring image data in a first domain. The acquired image data is transformed from the first domain into a second domain in which the acquired image data exhibits a high degree of sparsity. An initial set of transform coefficients is approximated for transforming the image data from the second domain into a third domain in which the image may be displayed. The approximated initial set of transform coefficients is updated based on a weighing of where substantial transform coefficients are likely to be located relative to the initial set of transform coefficients. An image is constructed in the third domain based on the updated set of transform coefficients. The constructed image is displayed.

摘要翻译： 一种用于构建图像的方法包括获取第一域中的图像数据。 所获取的图像数据从第一域变换到第二域，其中所获取的图像数据表现出高度的稀疏性。 近似变换系数的初始集合，用于将来自第二域的图像数据变换成可以显示图像的第三域。 基于对相对于初始变换系数集合可能存在实质变换系数的权重来更新近似初始变换系数集合。 基于更新的变换系数组，在第三域中构建图像。 显示构图。

公开(公告)号：US08582907B2

公开(公告)日：2013-11-12

申请号：US12938572

申请日：2010-11-03

申请人： Ali Bilgin ,  Yookyung Kim ,  Mariappan S. Nadar

发明人： Ali Bilgin ,  Yookyung Kim ,  Mariappan S. Nadar

IPC分类号： G06K9/46 ,  H04N7/12

CPC分类号： G06T9/00

摘要： A method for constructing an image includes acquiring image data in a sensing domain, transforming the acquired image data into a sparse domain, approximating sparse coefficients based on the transformed acquired image data, performing a Bayes Least Squares estimation on the sparse coefficients based on Gaussian Scale Mixtures Model to generate weights, approximating updated sparse coefficients by using the weights and acquired image, constructing an image based on the updated sparse coefficients, and displaying the constructed image.

摘要翻译： 一种用于构建图像的方法包括获取感测区域中的图像数据，将所获取的图像数据变换为稀疏域，基于变换获取的图像数据近似稀疏系数，对基于高斯标度的稀疏系数执行贝叶斯最小二乘估计 混合模型产生权重，通过使用权重和获取的图像近似更新的稀疏系数，基于更新的稀疏系数构建图像，并显示构造的图像。

公开(公告)号：US20120008843A1

公开(公告)日：2012-01-12

申请号：US12938572

申请日：2010-11-03

申请人： Ali Bilgin ,  Yookyung Kim ,  Mariappan S. Nadar

发明人： Ali Bilgin ,  Yookyung Kim ,  Mariappan S. Nadar

IPC分类号： G06K9/00

CPC分类号： G06T9/00

摘要： A method for constructing an image includes acquiring image data in a sensing domain, transforming the acquired image data into a sparse domain, approximating sparse coefficients based on the transformed acquired image data, performing a Bayes Least Squares estimation on the sparse coefficients based on Gaussian Scale Mixtures Model to generate weights, approximating updated sparse coefficients by using the weights and acquired image, constructing an image based on the updated sparse coefficients, and displaying the constructed image.

摘要翻译： 一种用于构建图像的方法包括获取感测区域中的图像数据，将所获取的图像数据变换为稀疏域，基于变换获取的图像数据近似稀疏系数，对基于高斯标度的稀疏系数执行贝叶斯最小二乘估计 混合模型产生权重，通过使用权重和获取的图像近似更新的稀疏系数，基于更新的稀疏系数构建图像，并显示构造的图像。

公开(公告)号：US08548797B2

公开(公告)日：2013-10-01

申请号：US12262145

申请日：2008-10-30

申请人： Yookyung Kim ,  Shuang Guo ,  Xian Xiang Hu ,  Xin Li

发明人： Yookyung Kim ,  Shuang Guo ,  Xian Xiang Hu ,  Xin Li

IPC分类号： G06F17/20 ,  G06F17/28 ,  G06F17/27 ,  G06F17/21 ,  G10L21/00

CPC分类号： G06F17/275

摘要： A content-providing entity receives a relatively short text from a user and attempts to determine, automatically, based on that short text (and on other available clues), a language that the user can read and understand. The content-providing entity may then provide, to the user, documents that are written in the determined language. The content-providing entity may determine a language of the input text based on several factors in combination: (a) the service provider's “market,” which is determined based on at least a portion of the URL of the Internet site to which the user directed his browser; (b) the user's “region,” which is determined based on the source Internet Protocol (IP) address of the IP packets that the user sends to the Internet site; (c) the “script” in which the short user-entered text is written; and (d) a statistical analysis of the frequency of the characters present in the short user-entered text.

摘要翻译： 内容提供实体从用户接收相对短的文本，并尝试基于该短文本（以及其他可用线索）来确定用户可以阅读和理解的语言。 然后，内容提供实体可以向用户提供以确定的语言书写的文档。 内容提供实体可以基于以下几个因素来确定输入文本的语言：（a）服务提供商的“市场”，其基于用户所在的因特网站点的URL的至少一部分来确定 指导他的浏览器 （b）基于用户发送到因特网站点的IP分组的源IP地址确定用户的“区域”; （c）写入短的用户输入的文本的“脚本”; 和（d）对短用户输入文本中存在的字符的频率的统计分析。

公开(公告)号：US20100114559A1

公开(公告)日：2010-05-06

申请号：US12262145

申请日：2008-10-30

申请人： Yookyung Kim ,  Shuang Guo ,  Xian Xiang Hu ,  Xin Li

发明人： Yookyung Kim ,  Shuang Guo ,  Xian Xiang Hu ,  Xin Li

IPC分类号： G06F17/20

CPC分类号： G06F17/275

摘要： A content-providing entity receives a relatively short text from a user and attempts to determine, automatically, based on that short text (and on other available clues), a language that the user can read and understand. The content-providing entity may then provide, to the user, documents that are written in the determined language. The content-providing entity may determine a language of the input text based on several factors in combination: (a) the service provider's “market,” which is determined based on at least a portion of the URL of the Internet site to which the user directed his browser; (b) the user's “region,” which is determined based on the source Internet Protocol (IP) address of the IP packets that the user sends to the Internet site; (c) the “script” in which the short user-entered text is written; and (d) a statistical analysis of the frequency of the characters present in the short user-entered text.

摘要翻译： 内容提供实体从用户接收相对短的文本，并尝试基于该短文本（以及其他可用的线索）来确定用户可以阅读和理解的语言。 然后，内容提供实体可以向用户提供以确定的语言书写的文档。 内容提供实体可以基于以下几个因素来确定输入文本的语言：（a）服务提供商的“市场”，其基于用户所在的因特网站点的URL的至少一部分来确定 指导他的浏览器 （b）基于用户发送到因特网站点的IP分组的源IP地址确定用户的“区域”; （c）写入短的用户输入的文本的“脚本”; 和（d）对短用户输入文本中存在的字符的频率的统计分析。

公开(公告)号：US20080154577A1

公开(公告)日：2008-06-26

申请号：US11645926

申请日：2006-12-26

申请人： Yookyung Kim ,  Jun Huang ,  Youssef Billawala

发明人： Yookyung Kim ,  Jun Huang ,  Youssef Billawala

IPC分类号： G06F17/28

CPC分类号： G06F17/2827 ,  G06F17/2775

摘要： Traditional statistical machine translation systems learn all information from a sentence aligned parallel text and are known to have problems translating between structurally diverse languages. To overcome this limitation, the present invention introduces two-level training, which incorporates syntactic chunking into statistical translation. A chunk-alignment step is inserted between the sentence-level and word-level training, which allows differing training for these two sources of information in order to learn lexical properties from the aligned chunks and learn structural properties from chunk sequences. The system consists of a linguistic processing step, two level training, and a decoding step which combines chunk translations of multiple sources and multiple language models.

摘要翻译： 传统的统计机器翻译系统从句子对齐的并行文本中学习所有信息，并且已知在不同结构语言之间翻译有问题。 为了克服这个限制，本发明引入了将句法分块结合到统计翻译中的两级训练。 在句子级和词级训练之间插入块对齐步骤，其允许针对这两个信息源的不同训练，以便从对齐的块学习词汇属性并从块序列学习结构特性。 该系统由语言处理步骤，两级训练和解码步骤组成，该步骤结合了多个来源和多种语言模型的块转换。

公开(公告)号：US08600979B2

公开(公告)日：2013-12-03

申请号：US12825304

申请日：2010-06-28

申请人： Yookyung Kim ,  Hongjian Zhao ,  Xin Li ,  Alexandra Levich ,  Tom Chi ,  Ming Sui ,  Yihong Zhao ,  Marc Davis

发明人： Yookyung Kim ,  Hongjian Zhao ,  Xin Li ,  Alexandra Levich ,  Tom Chi ,  Ming Sui ,  Yihong Zhao ,  Marc Davis

IPC分类号： G06F7/00

CPC分类号： G06F17/3089 ,  G06F17/30522

摘要： An online article is enhanced by displaying, in association with the article, supplemental content that includes entities that are extracted from the article and/or entities that are related to entities that are extracted from the article. The supplemental content further includes information about each of the entities. The information about an entity may be obtained by searching for the entity in one or more searchable repositories of data. For example, the supplemental content may include, for each entity, video, image, web, and/or news search results. The supplemental content may further include information such as stock quotes, abstracts, maps, scores, and so on. The entities are selected using a variety of analyses and ranking techniques based on contextual factors such as user-specific information, time-sensitive popularity trends, grammatical features, search result quality, and so on. The entities may further be selected for purposes such as generating ad-based revenue.

摘要翻译： 通过与文章相关联地显示包括从文章中提取的实体和/或与从文章中提取的实体相关的实体的补充内容来增强在线文章。 补充内容还包括关于每个实体的信息。 可以通过在一个或多个可搜索的数据库中搜索实体来获得关于实体的信息。 例如，对于每个实体，补充内容可以包括视频，图像，网络和/或新闻搜索结果。 补充内容还可以包括股票报价，摘要，地图，分数等信息。 使用各种基于上下文因素的分析和排序技术来选择实体，例如用户特定信息，时间敏感的人气趋势，语法特征，搜索结果质量等。 可以进一步选择实体，例如生成基于广告的收入。